Marketing would like to increase email campaign engagement by segmenting the customer-base using their buying habits.
The Data Science team has identified four customer segments. The segments were given descriptions based on the top product purchases within the segment.
Segment 1 Preferences: Mountain Bikes, Above $3,200 (Premium Models)
Segment 2 Preferences: Road Bikes, Above $3,200 (Premium Models)
Segment 3 Preferences: Road Bikes, Below $3,200 (Economical Models)
Segment 4 Preferences: Both Road and Mountain, Below $3,200 (Economical Models)
Our customer base consists of 30 bike shops. Based on the proportion of bikes purchased by category_1 and category_2, we can observe that several customers have strong preferences for Road or Mountain Bikes
This is a 2D projection based on customer similarity that exposes four clusters, which are key segments in the customer base.
The four customer segments were given descriptions based on the top product purchases within the segment.
Segment 1 Preferences: Mountain Bikes, Above $3,200 (Premium Models)
Segment 2 Preferences: Road Bikes, Above $3,200 (Premium Models)
Segment 3 Preferences: Road Bikes, Below $3,200 (Economical Models)
Segment 4 Preferences: Both Road and Mountain, Below $3,200 (Economical Models)